Individual Prognosis of Diabetes Long-term Risks: A CBR Approach

E. Armengol; A. Palaudàries; E. Plaza

doi:10.1055/s-0038-1634463

Methods of Information in Medicine, Inhaltsverzeichnis

Methods Inf Med 2001; 40(01): 46-51
DOI: 10.1055/s-0038-1634463

Original Article

Schattauer GmbH

Individual Prognosis of Diabetes Long-term Risks: A CBR Approach

E. Armengol

¹Artificial Intelligence Research Institute (IIIA-CSIC), Campus UAB, Bellaterra, Catalonia, Spain

,

A. Palaudàries

²Unitat d’Endocrinologia, Hospital de Mataró, Carretera de Cirera, Mataró, Catalonia, Spain

,

E. Plaza

¹Artificial Intelligence Research Institute (IIIA-CSIC), Campus UAB, Bellaterra, Catalonia, Spain

› Institutsangaben

Abstract

We present DIRAS, an application to support physicians in determining the risk of complications for individual diabetic patients. The risk pattern of each diabetic patient is obtained using a Case-based Reasoning method called LID. Case-based Reasoning is an Artificial Intelligence technique based on solving new situations according to past experiences. For each patient, the LID method determines the risk of each diabetic complication according to the risk of already diagnosed patients. In addition, LID builds a description that can be viewed as an explanation of the obtained risk.

Keywords

Diabetes Mellitus - Individual Prognosis - Artificial Intelligence - Case-based Reasoning

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Referenzen

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